Numeric data is often not conducive to direct analysis. In order to simplify the data analysis, charts and graphs are used to visually describe the data. Other methods have also been used to visually describe data including data coloration.
Data coloration is a process that maps colors to data points in order to provide a concise visual description of the data. The process is initiated by selecting a set of colors to be used in the image. The sets of colors used in these operations are called colormaps and standard applications allow a user to select among several different maps. Once the colormap has been selected, the software matches each of the data points to one of the colors in the color map. The data can then be displayed as a color image with each matrix entry represented by a colored area in the image.
It is often the case, however, that there are more data points than colors in the colormap, necessitating the mapping of several data points to a single color. Using the standard method, matrix entries with close data values will be mapped to the same or similar color, making it difficult to differentiate between the points very accurately. Additionally, the standard method fails to focus on the most important matrix entries, as each of the entries are treated equally. This prevents selective viewing of matrix values as necessitated by many forms of analysis.
In order to alleviate this problem, a method is needed that enables dynamic color mapping and display of numeric data. The method would ideally enable a user to select the most important data values while providing visual clarity between data points with similar values.